Simulation Modeling and Analysis with Arena

by Tayfur Altiok

Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment." It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings.

· Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems
· Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems
· Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
* Ample end-of-chapter problems and full Solutions Manual
* Includes CD with sample ARENA modeling programs

Paperback

First published June 18, 2007

Reviews

[Andrea Ratti · Rating 4 out of 5]

Useful book to anyone who wants to learn something about modeling complex systems with discrete-event simulation paradigm, at a basic level. The whole text can be considered like a full undergraduate simulation course or an introductory graduate simulation course; for graduated students, this book is also a very good reminder. On this way, some of the most critical topics concerning simulation are afforted, e.g. statistical output analysis and correlation analysis.

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